> That is a rather bold statement without proper evidence.
I based this on a couple of insights
1. OpenAI itself encourages adding examples to prompts where necessary. Given the same initial prompt, this means that the prompt with examples will elicit more specific results.
If the goal of a plugin is to be used by ChatGPT, then adding examples and exhaustively covering different conversational tracks in which that plugin can be used can only help.
> Is it universal or does the optimal length depend on the plugin complexity?
If the plugin is so trivial that it can be captured by a short description, then a longer description will not be necessary. It remains to be tested what ChatGPT will do if it is asked to choose between two identical plugins with short and long descriptions.
This gets to the heart of why optimizing for AI is so fascinating to me. You're working to attract a non-human intelligence to your door. Of course, I realize that Google's search algos are also AI infused so we have been doing this for years now but this is the first time I am actively thinking about how AI will pick my content over someone else's.
Yes, langchains and llama-index are both amazing techs.
They are separate from plug-ins though.
Plug-ins are ChatGPT specific (afaik) and are driven by free form content written by plug-in developers for ChatGPT.
Langchains start with human input, then go off to do their own thing without necessarily investing free form content written specifically for the model.
Llama-index starts with Freeform content written for people and makes it easier for the underlying model to read/infer from it.
The way I see it is that there used to be SEO to please the Pagerank. Soon, there will be GEO to please the generative engine.
I based this on a couple of insights
1. OpenAI itself encourages adding examples to prompts where necessary. Given the same initial prompt, this means that the prompt with examples will elicit more specific results.
If the goal of a plugin is to be used by ChatGPT, then adding examples and exhaustively covering different conversational tracks in which that plugin can be used can only help.
> Is it universal or does the optimal length depend on the plugin complexity?
If the plugin is so trivial that it can be captured by a short description, then a longer description will not be necessary. It remains to be tested what ChatGPT will do if it is asked to choose between two identical plugins with short and long descriptions.
This gets to the heart of why optimizing for AI is so fascinating to me. You're working to attract a non-human intelligence to your door. Of course, I realize that Google's search algos are also AI infused so we have been doing this for years now but this is the first time I am actively thinking about how AI will pick my content over someone else's.